Name
Comparison of different remote sensing methods in estimating evapotranspiration at an alpine juvenile forest in the Canadian Rockies
Date & Time
Monday, May 27, 2024, 10:45 AM - 11:00 AM
Description

As vegetation changes in response to climate change, hydrological processes in Canadian Rocky Mountain headwater basins will also change. Mountain water supplies, which supply water to much of Western Canada, depend on the connection between subalpine forest hydrological processes and ecological function because these processes regulate evapotranspiration (ET), the primary water loss from these systems. Understanding how shifting ET is influenced by recent climate changes is crucial for comprehending their impact on water resources in the mountain headwaters of the Canadian Rockies. To achieve this, ET was measured with Eddy Covariance at a subalpine forest at Fortress Ridge South, Kananaskis, Alberta, in the Canadian Rockies during eight dissimilar growing seasons (early spring to later summer between 2017 and 2023). However, traditional ways of measuring ET (e.g. eddy covariance) have limitation due to data availability, scale representation, and forest conditions. Leveraging public remote sensing data (e.g Sentinel 2) can provide valuable comparative data against observational records, aiding in rigorously testing relationships between remote sensing indices (such as NDVI and VARI) and ground-measured ET. Preliminary results have shown the highest R2 when using VARI from Sentinel 2 (0.54) and Landsat 8 (0.72) to estimate daily ET between 2016 and 2019. While NDVI also yielded an R2 of 0.34 with Sentinel 2 and 0.59 with Landsat 8. Therefore, significant relations such as VARI and NDVI can be used to estimate ET in a similar subalpine forest, which provides potential to monitor alpine forest hydrological processes at a larger scale in the Canadian Rockies.

Location Name
Conference Room - 2224
Full Address
Carleton University - Richcraft Hall
1125 Colonel By Dr
Ottawa ON K1S 5B6
Canada
Session Type
Breakout Session